Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla.

To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.

A 128-channel receive array for cortical brain imaging at 7 T.

PURPOSE: A 128-channel receive-only array for brain imaging at 7 T was simulated, designed, constructed, and tested within a high-performance head gradient designed for high-resolution functional imaging. METHODS: The coil used a tight-fitting helmet geometry populated with 128 loop elements and preamplifiers to fit into a 39 cm diameter space inside a built-in gradient. The signal-to-noise ratio (SNR) and parallel imaging performance (1/g) were measured in vivo and simulated using electromagnetic modeling. The histogram of 1/g factors was analyzed to assess the range of performance. The array's performance was compared to the industry-standard 32-channel receive array and a 64-channel research array. RESULTS: It was possible to construct the 128-channel array with body noise-dominated loops producing an average noise correlation of 5.4%. Measurements showed increased sensitivity compared with the 32-channel and 64-channel array through a combination of higher intrinsic SNR and g-factor improvements. For unaccelerated imaging, the 128-channel array showed SNR gains of 17.6% and 9.3% compared to the 32-channel and 64-channel array, respectively, at the center of the brain and 42% and 18% higher SNR in the peripheral brain regions including the cortex. For R = 5 accelerated imaging, these gains were 44.2% and 24.3% at the brain center and 86.7% and 48.7% in the cortex. The 1/g-factor histograms show both an improved mean and a tighter distribution by increasing the channel count, with both effects becoming more pronounced at higher accelerations. CONCLUSION: The experimental results confirm that increasing the channel count to 128 channels is beneficial for 7T brain imaging, both for increasing SNR in peripheral brain regions and for accelerated imaging.

Software Training in HEP.

The long-term sustainability of the high-energy physics (HEP) research software ecosystem is essential to the field. With new facilities and upgrades coming online throughout the 2020s, this will only become increasingly important. Meeting the sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required software skills fall into three broad groups. The first is fundamental and generic software engineering (e.g., Unix, version control, C++, and continuous integration). The second is knowledge of domain-specific HEP packages and practices (e.g., the ROOT data format and analysis framework). The third is more advanced knowledge involving specialized techniques, including parallel programming, machine learning and data science tools, and techniques to maintain software projects at all scales. This paper discusses the collective software training program in HEP led by the HEP Software Foundation (HSF) and the Institute for Research and Innovation in Software in HEP (IRIS-HEP). The program equips participants with an array of software skills that serve as ingredients for the solution of HEP computing challenges. Beyond serving the community by ensuring that members are able to pursue research goals, the program serves individuals by providing intellectual capital and transferable skills important to careers in the realm of software and computing, inside or outside HEP.

k-Space Domain Parallel Transmit Pulse Design.

PURPOSE: To accelerate the design of (under- or oversampled) multidimensional parallel transmission pulses. METHODS: A k-space domain parallel transmission pulse design algorithm was proposed that produces a sparse matrix relating a complex-valued target excitation pattern to the pulses that produce it, and can be finely parallelized. The algorithm was applied in simulations to the design of 3D SPINS pulses for inner volume excitation in the brain at 7 Tesla. It was characterized in terms of the dependence of computation time, excitation error, and required memory on algorithm parameters, and it was compared to an iterative spatial domain pulse design method in terms of computation time, excitation error, Gibbs ringing, and ability to compensate off-resonance. RESULTS: The proposed algorithm achieved approximately 80% faster pulse design compared to the spatial domain method with the same number of parallel threads, with the tradeoff of increased excitation error and RMS RF amplitude. It reduced the memory required to store the design matrix by 99% compared to a full matrix solution. Even with a coarse design grid, the algorithm produced patterns that were free of Gibbs ringing. It was similarly sensitive to k-space undersampling as the spatial domain method, and was similarly capable of compensating for off-resonance. CONCLUSIONS: The proposed k-space domain algorithm accelerates and finely parallelizes parallel transmission pulse design, with a modest tradeoff of excitation error and RMS RF amplitude.

RF coils: A practical guide for nonphysicists.

Radiofrequency (RF) coils are an essential MRI hardware component. They directly impact the spatial and temporal resolution, sensitivity, and uniformity in MRI. Advances in RF hardware have resulted in a variety of designs optimized for specific clinical applications. RF coils are the "antennas" of the MRI system and have two functions: first, to excite the magnetization by broadcasting the RF power (Tx-Coil) and second to receive the signal from the excited spins (Rx-Coil). Transmit RF Coils emit magnetic field pulses ( B1+) to rotate the net magnetization away from its alignment with the main magnetic field (B0 ), resulting in a transverse precessing magnetization. Due to the precession around the static main magnetic field, the magnetic flux in the receive RF Coil ( B1-) changes, which generates a current I. This signal is "picked-up" by an antenna and preamplified, usually mixed down to a lower frequency, digitized, and processed by a computer to finally reconstruct an image or a spectrum. Transmit and receive functionality can be combined in one RF Coil (Tx/Rx Coils). This review looks at the fundamental principles of an MRI RF coil from the perspective of clinicians and MR technicians and summarizes the current advances and developments in technology. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 6.